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Record W2035094740 · doi:10.1177/153331750602100105

Computerized cognitive testing battery identifies mild cognitive impairment and mild dementia even in the presence of depressive symptoms

2006· article· en· W2035094740 on OpenAlexaff
Glen M. Doniger, Tzvi Dwolatzky, David M. Zucker, Howard Chertkow, Howard Crystal, Avraham Schweiger, Ely S. Simon

Bibliographic record

VenueAmerican Journal of Alzheimer s Disease & Other Dementias® · 2006
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsMcGill University
Fundersnot available
KeywordsGeriatric Depression ScaleDementiaCognitionDepression (economics)PsychologyClinical psychologyDepressive symptomsPsychiatryAudiologyMedicineDiseaseInternal medicine

Abstract

fetched live from OpenAlex

Cognitive and depressive symptoms co-occur, complicating detection of mild cognitive impairment (MCI) and early dementia. In this study, discriminant validity of a novel computerized cognitive battery for MCI detection was evaluated after covariation for depressive symptom severity. In addition to the computerized battery, participants at two sites received the 30-item self-administered Geriatric Depression Scale (GDS; n=72); those at two other centers received the observer-administered Cornell Scale for Depression in Dementia (CSDD; n=88). In both cohorts, a Global Cognitive Score and memory, executive function, visual spatial, and verbal index scores discriminated among cognitively healthy, MCI, and mild dementia groups after covariation for GDS or CSDD, respectively (p < 0.05). Thus, the computerized battery for detection of mild impairment is robust to comorbid depressive symptoms, supporting its clinical utility in identifying neurodegenerative disease even in elderly with depression.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.022
GPT teacher head0.303
Teacher spread0.282 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations77
Published2006
Admission routes1
Has abstractyes

Explore more

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